Gao Yin-Han
Laboratory of Automobile Simulation and Control, Jilin University, 130022, Changchun, Jilin, China
Wang Tian-Hao
Laboratory of Automobile Simulation and Control, Jilin University, 130022, Changchun, Jilin, China
Yang Kai-Yu
Laboratory of Automobile Simulation and Control, Jilin University, 130022, Changchun, Jilin, China
Zhang Jun-Dong
Laboratory of Automobile Simulation and Control, Jilin University, 130022, Changchun, Jilin, China
Song Yu-He
Laboratory of Automobile Simulation and Control, Jilin University, 130022, Changchun, Jilin, China
Jia Yan-Mei
Laboratory of Automobile Simulation and Control, Jilin University, 130022, Changchun, Jilin, China
ABSTRACT
The randomness of automobile cable bundles position brought by different installation and automobile motion, leading to cable bundles crosstalk has the dynamic range, using statistics principle to obtain the mean and deviation of dynamic cable bundles crosstalk, under the confidence level of 80% obtained the confidence interval of cable bundles dynamic crosstalk. Using this method improved the dynamic crosstalk range of the original best, worst case method. At the same time, comparing the simulation results of 273 times Random Displacement Spline Interpolation (RDSI) and the improved interval, verified the accuracy and reliability of the model. Under the condition of low frequency, the generated results of 273 times RDSI algorithm all fall in to improved the range and improved interval compared with the original interval shrank by 76%, largely improves the prediction precision, at the same time this method is simple, convenient, according to the different precision requirement, it can quickly predict dynamic crosstalk of automobile cable bundles.
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How to cite this article
Gao Yin-Han, Wang Tian-Hao, Yang Kai-Yu, Zhang Jun-Dong, Song Yu-He and Jia Yan-Mei, 2013. Improvement of the Best and the Worst Case Method on the Automobile
Cable Bundles Dynamic Crosstalk Based on the Statistical Model. Journal of Applied Sciences, 13: 3330-3334.
DOI: 10.3923/jas.2013.3330.3334
URL: https://scialert.net/abstract/?doi=jas.2013.3330.3334
DOI: 10.3923/jas.2013.3330.3334
URL: https://scialert.net/abstract/?doi=jas.2013.3330.3334
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